Optimal ski route selection is a challenge based on a multitude of factors, such as the steepness, compass direction, or crowdedness. The personal preferences of every skier towards these factors require individual adaptations, which aggravate this task. Current approaches within this domain do not combine automated routing capabilities with user preferences, missing out on the possibility of integrating domain knowledge in the analysis process. We introduce SkiVis, a visual analytics application to interactively explore ski slopes and provide routing recommendations based on user preferences. In collaboration with ski guides and enthusiasts, we elicited requirements and guidelines for such an application and propose different workflows depending on the skiers' familiarity with the resort. In a case study on the resort of Ski Arlberg, we illustrate how to leverage volunteered geographic information to enable a numerical comparison between slopes. We evaluated our approach through a pair-analytics study and demonstrate how it supports skiers in discovering relevant and preference-based ski routes. Besides the tasks investigated in the study, we derive additional use cases from the interviews that showcase the further potential of SkiVis, and contribute directions for further research opportunities.

翻译：摘要：最优滑雪路线选择是一项基于多种因素（如坡度陡峭程度、朝向或拥挤度）的挑战。每位滑雪者对这些因素的个人偏好需要个体化调整，这进一步加剧了任务的复杂性。当前该领域的方法未能将自动路线规划能力与用户偏好相结合，从而错失了在分析过程中整合领域知识的可能性。我们提出SkiVis，一个用于交互式探索滑雪坡道并根据用户偏好提供路线推荐的可视分析应用。通过与滑雪向导及爱好者的合作，我们梳理了此类应用的需求与设计准则，并根据滑雪者对度假村的熟悉程度提出了不同的工作流程。在针对Ski Arlberg度假村的案例研究中，我们展示了如何利用志愿地理信息实现坡道之间的数值比较。通过双人分析研究评估了该方法，并证明了它如何帮助滑雪者发现相关且符合偏好的滑雪路线。除研究中探讨的任务外，我们还从访谈中衍生出额外用例，展示了SkiVis的进一步潜力，并为未来研究方向提供了建议。